A generic Model Context Protocol (MCP) server for high-accuracy document reranking using sentence-transformers (Cross-Encoder). Ideal for enhancing RAG and AI agent decision-making. sentence-transformers (Cross-Encoder) を使用して文書の関連度を再計算・ソートする汎用 MCP (Model Context Protocol) サーバー。
A local MCP server for RAG memory, semantic search, and context optimization using Ollama and SQLite. It serves as a central hub that manages document embeddings, text compression, and proxies calls to other sub-MCP servers.
Local MCP server for token optimization, providing tools to compress code/JSON, optimize prompts, and manage placeholder-based content redaction and hydration to reduce LLM token usage.
